Engineering topics

Borak, Jordan

Publications and source records attributed to Borak, Jordan.

5 records

NASA NTRS2012

Distributed Assimilation of Satellite-based Snow Extent for Improving Simulated Streamflow in Mountainous, Dense Forests: An Example Over the DMIP2 Western Basins

Snow cover area affects snowmelt, soil moisture, evapotranspiration, and ultimately streamflow. For the Distributed Model Intercomparison Project - Phase 2 Western basins, we assimilate satellite-based fractional snow cover area (fSCA) from the Moderate Resolution Imaging Spectroradiometer, or MODIS, into the National Weather Service (NWS) SNOW-17 model. This model is coupled with the NWS Sacramento Heat Transfer (SAC-HT) model inside the National Aeronautics and Space Administration's (NASA) Land Information System. SNOW-17 computes fSCA from snow water equivalent (SWE) values using an areal depletion curve. Using a direct insertion, we assimilate fSCAs in two fully distributed ways: 1) we update the curve by attempting SWE preservation, and 2) we reconstruct SWEs using the curve. The preceding are refinements of an existing simple, conceptually-guided NWS algorithm. Satellite fSCA over dense forests inadequately accounts for below-canopy snow, degrading simulated streamflow upon assimilation during snowmelt. Accordingly, we implement a below-canopy allowance during assimilation. This simplistic allowance and direct insertion are found to be inadequate for improving calibrated results, still degrading them as mentioned above. However, for streamflow volume for the uncalibrated runs, we obtain: (1) substantial to major improvements (64-81 %) as a percentage of the control run residuals (or distance from observations), and (2) minor improvements (16-22 %) as a percentage of observed values. We highlight the need for detailed representations of canopy-snow optical radiative transfer processes in mountainous, dense forest regions if assimilation-based improvements are to be seen in calibrated runs over these areas.

Yatheendradas, Soni↗

NASA NTRS2011

Numerical Model Sensitivity to Heterogeneous Satellite Derived Vegetation Roughness

The sensitivity of a mesoscale weather prediction model to a 1 km satellite-based vegetation roughness initialization is investigated for a domain within the south central United States. Three different roughness databases are employed: i) a control or standard lookup table roughness that is a function only of land cover type, ii) a spatially heterogeneous roughness database, specific to the domain, that was previously derived using a physically based procedure and Moderate Resolution Imaging Spectroradiometer (MODIS) imagery, and iii) a MODIS climatologic roughness database that like (i) is a function only of land cover type, but possesses domain specific mean values from (ii). The model used is the Weather Research and Forecast Model (WRF) coupled to the Community Land Model within the Land Information System (LIS). For each simulation, a statistical comparison is made between modeled results and ground observations within a domain including Oklahoma, Eastern Arkansas, and Northwest Louisiana during a 4-day period within IHOP 2002. Sensitivity analysis compares the impact the three roughness initializations on time-series temperature, precipitation probability of detection (POD), average wind speed, boundary layer height, and turbulent kinetic energy (TKE). Overall, the results indicate that, for the current investigation, replacement of the standard look-up table values with the satellite-derived values statistically improves model performance for most observed variables. Such natural roughness heterogeneity enhances the surface wind speed, PBL height and TKE production up to 10 percent, with a lesser effect over grassland, and greater effect over mixed land cover domains.

Jasinski, Michael↗

NASA NTRS2010

Influence of Satellite-Based Heterogeneous Vegetation Momentum Roughness on Mesoscale Model Dynamics During IHOP 2002

The sensitivity of mesoscale weather prediction model to a vegetation roughness initialization is investigated for the south central United States. Three different roughness databases are employed: i) a control or standard lookup table roughness that is a function only of land cover type, ii) a spatially heterogeneous roughness database previously derived using a physically based procedure and MODIS imagery, and iii) a MODIS climatologic roughness database that possesses the same spatial heterogeneity as (i) but with mean land class values from (ii). The model used is the Weather Research and Forecast Model (WRF) coupled to the Community Land Model within the Land Information System (LIS). For each simulation, a statistical comparison is made between modeled results and ground observations from meteorological stations within the Oklahoma mesonet and surrounding region during IHOP20O2. A sensitivity analysis on the impact the MODIS-based roughness fields is also made through a time-series intercomparison of temperature bias, probability of detection (POD), average wind speed, boundary layer height, and turbulent kinetic energy (TKE) the results that, for the current replacement of the standard land-cover type based roughness values with the satellite-derived fields statistically improves model performance for most of the observed variables. Further, the satellite-based roughness enhances the surface wind speed, PBL height and TKE production on the order of 3 to l0 percent, with a lesser effect over grassland and cropland domains, and the greater effect over mixed land cover domains

Jasinski, Michael↗

NASA NTRS2007

Evaluation of a Potential for Enhancing the Decision Support System of the Interagency Modeling and Atmospheric Assessment Center with NASA Earth Science Research Results

NASA's objective for the Applied Sciences Program of the Science Mission Directorate is to expand and accelerate the realization of economic and societal benefits from Earth science, information, and technology. This objective is accomplished by using a systems approach to facilitate the incorporation of Earth observations and predictions into the decision-support tools used by partner organizations to provide essential services to society. The services include management of forest fires, coastal zones, agriculture, weather prediction, hazard mitigation, aviation safety, and homeland security. In this way, NASA's long-term research programs yield near-term, practical benefits to society. The Applied Sciences Program relies heavily on forging partnerships with other Federal agencies to accomplish its objectives. NASA chooses to partner with agencies that have existing connections with end-users, information infrastructure already in place, and decision support systems that can be enhanced by the Earth science information that NASA is uniquely poised to provide (NASA, 2004).

Blonski, Slawomir↗

NASA NTRS2005

Bulk Surface Momentum Parameters for Satellite-Derived Vegetation Fields

The bulk aerodynamic parameters associated with the absorption of surface momentum by vegetated landscapes are theoretically estimated within the context of Raupach's roughness sublayer formulation. The parameters include the bulk plant drag coefficient, maximum u*/U(sub h), sheltering coefficient, and canopy area density at onset of sheltering. Parameters are estimated for the four principal IGBP land cover classes within the U.S. Southern Great Plains: evergreen needleleaf forests, grasslands, croplands, and open shrublands. The estimation approach applies the Method of Moments to roughness data from several international field experiments and other published sources. The results provide the necessary land surface parameters for satellite-based estimation of momentum aerodynamic roughness length and zero-plane displacement height for seasonally variable vegetation fields employed in most terrestrial and atmospheric simulation models used today. Construction of sample displacement and roughness maps over the Southern United States using MODIS land products demonstrates the potential of this approach for regional to global applications.

Jasinski, Michael F.↗